Fligner’s test tests the null hypothesis that all input samples
are from populations with equal variances. Fligner’s test is
non-parametric in contrast to Bartlett’s test bartlett and
Levene’s test levene.

Parameters:

sample1, sample2, ... : array_like

arrays of sample data. Need not be the same length

center : {‘mean’, ‘median’, ‘trimmed’}, optional

keyword argument controlling which function of the data
is used in computing the test statistic. The default
is ‘median’.

proportiontocut : float, optional

When center is ‘trimmed’, this gives the proportion of data points
to cut from each end. (See scipy.stats.trim_mean.)
Default is 0.05.

Returns:

Xsq : float

the test statistic

p-value : float

the p-value for the hypothesis test

Notes

As with Levene’s test there are three variants
of Fligner’s test that differ by the measure of central
tendency used in the test. See levene for more information.